Probabilistic Modeling of Insider Threat Detection Systems. - Brian E. Ruttenberg; Dave Blumstein; Jeff Druce; Michael Howard; Fred Reed; Leslie Wilfong; Crystal Lister; Steve Gaskin; Meaghan Foley; Daniel Scofield (GraMSec@CSF, 2017)

Predicting observable and occult injuries in trauma patients from sparse measurements. - Jeff Druce; Max Metzger; Nidhi Gupta; Rishi Kundi (AIH@IJCAI, 2018)

Causal Learning and Explanation of Deep Neural Networks via Autoencoded Activations. - Michael Harradon; Jeff Druce; Brian E. Ruttenberg (CoRR, 2018)

Privacy preserving Neural Network Inference on Encrypted Data with GPUs. - Daniel Takabi; Robert Podschwadt; Jeff Druce; Curt Wu; Kevin Procopio (CoRR, 2019)

Improving the Performance of Fine-Grain Image Classifiers via Generative Data Augmentation. - Shashank Manjunath; Aitzaz Nathaniel; Jeff Druce; Stan German (CoRR, 2020)

Explainable Artificial Intelligence (XAI) for Increasing User Trust in Deep Reinforcement Learning Driven Autonomous Systems. - Jeff Druce; Michael Harradon; James Tittle (CoRR, 2021)

Brittle AI, Causal Confusion, and Bad Mental Models: Challenges and Successes in the XAI Program. - Jeff Druce; James Niehaus; Vanessa Moody; David D. Jensen; Michael L. Littman (CoRR, 2021)